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Optimization of surface roughness in an end-milling operation using nested experimental design

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Abstract

This paper presents an experimental study to optimize the surface quality of an end-milled surface on a Vertical Machining Centre using Taguchi’s nested experimental design. The effect of various machining parameters on surface roughness was investigated on two different work piece materials, Aluminium alloy and Plain Carbon Steel. Other control factors, namely, feed rate and spindle speed, depth of cut and radial engagement of tool were varied in the experiment to measure surface roughness at four different positions on the work piece. Position was taken as an uncontrollable noise factor. Depth of cut was observed to be the most significant factor that affecting the surface roughness. Also, better surface finish was obtained while machining aluminum alloy as compared to plain carbon steel. Spindle speed and feed rate were the other two significant factors while machining aluminum alloy parts, although these factors did not significantly affect the finish for steel. Radial engagement of tool had no impact on the surface finish for aluminium alloy, while it had a significant impact for plain carbon steel. Further, the analysis of results shows that position P2 (middle of the milled surface) had the best surface finish while position P1 (at beginning of the cut) had relatively poorer finish.

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References

  1. Yalçın B, Özgür AE, Koru M (2009) The effects of various cooling strategies on surface roughness and tool wear during soft materials milling. J Mater Des 30(3):896–899. doi:10.1016/j.matdes.2008.05.037

    Google Scholar 

  2. Prakasvudhisarn C, Kunnapapdeelert S, Yenradee P (2009) Optimal cutting condition determination for desired surface roughness in end milling. Int J Adv Manuf Technol 41(5–6):440–451. doi:10.1007/s00170-008-1491-8

    Article  Google Scholar 

  3. Routara BC,. Bandyopadhyay A, Sahoo P (2009) Roughness modeling and optimization in CNC end milling using response surface method: effect of workpiece material variation. Int J Adv Manuf Technol 40(11–12): 1166–1180, doi: 10.1007/s00170-008-1440-6

  4. Ryu SH, Choi DK, Chu CN (2006) Roughness and texture generation on end milled surfaces. Int J Mach Tools Manuf 46:404–412

    Article  Google Scholar 

  5. Lou SJ, Chen JC (1997) In-process surface recognition of a CNC milling machine using the fuzzy nets method. Comp and Indl Engg 33(1–2):401–404

    Article  Google Scholar 

  6. Zhang JZ, Chenb JC, Kirby ED (2007) Surface roughness optimization in an end-milling operation using the Taguchi design method. J Mater Process Technol 184:233–239

    Article  Google Scholar 

  7. Chevrier P, Tidu A, Bolle B, Cezard P, Tinnes JP (2003) Investigation of surface integrity in high speed end milling of a low alloyed steel. Int J Mach Tools Manuf 43:1135–1142

    Article  Google Scholar 

  8. Ho Wen-Hsien, Tsai Jinn-Tsong, Lin Bor-Tsuen, Chou Jyh-Horng (2008) Adaptive network-based fuzzy inference system for prediction of surface roughness in end milling process using hybrid Taguchi-genetic learning algorithm. J Expert Sys with Appln. doi:10.1016/j.eswa.2008.01.051

  9. Gologlu C, Sakarya N (2008) The effects of cutter path strategies on surface roughness of pocket milling of 1.2738 steel based on Taguchi method. J Mater Process Technol 206:7–15

    Article  Google Scholar 

  10. Amina Nurul AKM, Dolaha SB, Mahmuda MB, Lajis MA (2008) Effects of workpiece preheating on surface roughness, chatter and tool performance during end milling of hardened steel D2. J Mater Process Technol 201:466–470

    Article  Google Scholar 

  11. Rahman M, Senthil Kumar A, Manzoor-Ul-Salam LingMS (2003) Effect of chilled air on machining performance in end milling. Int J Adv Manuf Technol 21:787–795

    Article  Google Scholar 

  12. Ryu SH, Choi DK, Chu CN (2006) Roughness and texture generation on end milled surfaces. Int J Mach Tools Manuf 46:404–412

    Article  Google Scholar 

  13. Bagci E, Aykut S (2006) A study of Taguchi optimization method for identifying optimum surface roughness in CNC face milling of cobalt based alloy. Int J Adv Manuf Technol 29:940–947

    Article  Google Scholar 

  14. Chang CK, Lu HS (2007) Design optimization of cutting parameters for side milling operations with multiple performance characteristics. Int J Adv Manuf Technol 32:18–26

    Article  Google Scholar 

  15. Smith GT (2002) Industrial metrology––surfaces and roundness. Springer, London

    Google Scholar 

  16. Ross PJ (1995) Taguchi techniques for quality engineering, 2nd edn. McGraw-Hill, New York

    Google Scholar 

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Authors and Affiliations

  1. Mechanical and Mechatronics Engineering Department, University of Waterloo, Waterloo, ON, Canada

    Kandarp Patel

  2. Mechanical Engineering Department, Thapar University, Patiala, 147004, Punjab, India

    Ajay Batish

  3. Mechanical Engineering Department, Thapar University, Patiala, 147004, Punjab, India

    Anirban Bhattacharya

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  1. Kandarp Patel
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  2. Ajay Batish
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  3. Anirban Bhattacharya
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Correspondence to Ajay Batish.

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Patel, K., Batish, A. & Bhattacharya, A. Optimization of surface roughness in an end-milling operation using nested experimental design. Prod. Eng. Res. Devel. 3, 361 (2009). https://doi.org/10.1007/s11740-009-0177-x

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  • DOI: https://doi.org/10.1007/s11740-009-0177-x

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